Automate Timetable Scheduling with AI: A Review
dc.contributor.author | Gajanayake, CLTH | |
dc.contributor.author | Pemarathne, WPJ | |
dc.date.accessioned | 2020-12-31T22:33:01Z | |
dc.date.available | 2020-12-31T22:33:01Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | http://ir.kdu.ac.lk/handle/345/3010 | |
dc.description | Article Full Text | en_US |
dc.description.abstract | Scheduling timetables are one of the complex and time-consuming process when constructing using manual methods. These manual methods don’t always promise the optimum schedule plan and leads to countless conflicts. Recently, there are many states of the art systems proposed for the task scheduling using Artificial Intelligence (AI). This paper reviews the recently propose timetable scheduling systems with AI. The result of the analysis shown that the evolutionary techniques has been used in many studies to generate optimize timetable schedule specially using the Genetic Algorithm. Most of the studies proved that the Genetic Algorithm optimizes most of the constraint and fitted to automate timetable scheduling. | en_US |
dc.language.iso | en | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Timetable Automation | en_US |
dc.subject | Artificial Intelligence | en_US |
dc.subject | Genetic Algorithm | en_US |
dc.title | Automate Timetable Scheduling with AI: A Review | en_US |
dc.type | Article Full Text | en_US |
dc.identifier.journal | KDU-IRC-2020 | en_US |
dc.identifier.pgnos | 523-528 | en_US |
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Computer Science [66]